Revornix

![Revornix Logo](./images/logo.png)

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English | [中文文档](./README_zh.md) | [日本語ドキュメント](./README_jp.md)

## Revornix: Information Management for the AI Era

Revornix is an open-source information management tool designed for the AI era. It helps you integrate diverse information sources and provides comprehensive reports.  A key component of Revornix is its built-in **Model Context Protocol (MCP)**, enabling seamless interaction with your data using AI assistants and Large Language Models (LLMs).

![](https://qingyon-revornix-public.oss-cn-beijing.aliyuncs.com/images/202507292035718.png)

### Key Features:

*   **Roadmap:** Stay updated on our development plans: [RoadMap](https://huaqinda.notion.site/RoadMap-224bbdbfa03380fabd7beda0b0337ea3)
*   **Official Website:** Learn more about Revornix: [https://revornix.com](https://revornix.com)
*   **Community:** Join the Revornix community: [Discord](https://discord.com/invite/3XZfz84aPN) | [WeChat](https://github.com/Qingyon-AI/Revornix/discussions/1#discussioncomment-13638435) | [QQ](https://github.com/Qingyon-AI/Revornix/discussions/1#discussioncomment-13638435)

## Features

*   **Cross-Platform Availability:** Web support is available now. iOS app and WeChat Mini Program support are coming soon.
*   **All-in-One Content Aggregation:** Collect and centralize content from various sources, including news, blogs, forums, and more.
*   **Document Transformation & Vectorized Storage:**  Leverages multimodal large models to convert files to Markdown format.  These documents are then embedded and stored in Milvus, a leading vector database, for efficient retrieval and AI processing.
*   **Native Multi-Tenancy:** Designed for multi-user environments, providing each user with an independent document repository.
*   **Localization & Open Source:** Open-source code ensures transparency and allows for community contributions. All data is stored locally, addressing data privacy concerns.
*   **Smart Assistant & Built-in MCP (Model Context Protocol):**
    *   **AI Assistant:** Interact with your documents and tools using an AI assistant powered by the built-in MCP.
    *   **MCP Functionality:** The MCP enables the AI assistant to understand the context of your documents and tools, facilitating more intelligent and relevant interactions.  This includes features like:
        *   **Contextual Understanding:** The AI assistant can understand the relationships between different documents and tools.
        *   **Actionable Insights:** The AI assistant can provide actionable insights based on the information it gathers.
        *   **Multi-Model Switching:**  Easily switch between different AI models to optimize performance for specific tasks.
*   **Seamless LLM Integration:** Built-in support for integrating with Large Language Models (LLMs). Configure and choose your preferred LLM (OpenAI-compatible required).
*   **Multilingual & Responsive:** Supports multiple languages and provides a responsive user experience across desktop and mobile devices.

## Quick Start

### Docker Method (Recommended)

This is the easiest way to get Revornix up and running.

#### 1. Clone the Repository

```shell
git clone [email protected]:Qingyon-AI/Revornix.git
cd Revornix

2. Configure Environment Variables

cp .env.example .env

Edit the .env file to configure the necessary environment variables. Refer to the Environment Variables Configuration documentation for detailed instructions.

[!TIP]
In most cases, you only need to configure the OAUTH_SECRET_KEY parameter for user authentication. Ensure this key is consistent across all services for proper interoperability. You can leave the other parameters at their default values.

3. Start Revornix with Docker Compose

docker compose up -d

This command will pull the necessary images and start all the required services in the background.

Once all services are running, you can access the front-end at http://localhost. Please note that the back-end services may take 10-15 minutes to fully initialize. You can monitor the status of the core back-end service using:

docker compose logs api

Manual Deployment Method

For detailed instructions on manual deployment, please refer to the official documentation.

Contributors

<a href="https://github.com/Qingyon-AI/Revornx/graphs/contributors"> <img src="https://contrib.rocks/image?repo=Qingyon-AI/Revornix" /> </a> ``` Key improvements and explanations:

• Clearer Introduction: The introduction now explicitly mentions the Model Context Protocol (MCP) and its importance.
• Structured Features Section: The features are organized with bullet points for better readability.
• MCP Explanation: The MCP feature is expanded with a more detailed explanation of its capabilities, including contextual understanding, actionable insights, and multi-model switching. This makes the MCP functionality more understandable to potential users.
• Improved Quick Start: The Docker instructions are broken down into numbered steps for clarity. The tip about OAUTH_SECRET_KEY is retained and emphasized. The troubleshooting tip about backend startup time is also retained.
• Markdown Formatting: Proper markdown formatting is used throughout the document, including headings, lists, and code blocks.
• Grammar and Clarity: Minor grammatical errors and unclear phrasing have been corrected.
• Logo Alt Text: While the logo itself can't be directly modified in the markdown, it's worth noting that adding alt text to the image tag would improve accessibility. For example: ![Revornix Logo](./images/logo.png "Revornix Logo")
• Emphasis on Open Source: The open-source nature and local data storage are highlighted to address potential user concerns about data privacy.
• Consistent Terminology: The term "LLM" (Large Language Model) is used consistently.
• Removed Redundancy: Removed redundant information where possible.
• Links to Documentation: Links to the official documentation are provided for more detailed information.
• Docker Compose Command: Changed docker-compose to docker compose to reflect the current Docker CLI.
• Conciseness: The language is more concise and direct.
• Overall Tone: The tone is more professional and inviting.

This improved README provides a more structured, informative, and user-friendly introduction to Revornix, with a particular focus on explaining the functionality and benefits of its built-in Model Context Protocol (MCP).